我正在尝试使用具有不连续x轴的pyplot创建一个图。通常的绘制方法是轴将具有以下内容:
(值)----//----(后值)
////表示您正在跳过(值)和(后值)之间的所有内容。
我还没有找到任何这样的例子，所以我想知道是否有可能。我知道您可以合并不连续的数据，例如财务数据，但我想使轴上的跳跃更明确。目前，我只是在使用子图，但我真的很希望最终所有内容都在同一张图上。
最佳答案
保罗的答案是做到这一点的完美方法。
但是，如果您不想进行自定义转换，则可以仅使用两个子图来创建相同的效果。
matplotlib示例中没有an excellent example of this written by Paul Ivanov而不是从头开始编写示例(它仅在当前的git技巧中，因为它仅在几个月前才提交。尚未在网页上。)。
这只是此示例的简单修改，具有不连续的x轴而不是y轴。 (这就是为什么我要将此帖子设为CW)
基本上，您只需要执行以下操作:
import matplotlib.pylab as plt
import numpy as np
# If you're not familiar with np.r_, don't worry too much about this. It's just
# a series with points from 0 to 1 spaced at 0.1, and 9 to 10 with the same spacing.
x = np.r_[0:1:0.1, 9:10:0.1]
y = np.sin(x)
fig,(ax,ax2) = plt.subplots(1, 2, sharey=True)
# plot the same data on both axes
ax.plot(x, y, 'bo')
ax2.plot(x, y, 'bo')
# zoom-in / limit the view to different portions of the data
ax.set_xlim(0,1) # most of the data
ax2.set_xlim(9,10) # outliers only
# hide the spines between ax and ax2
ax.spines['right'].set_visible(False)
ax2.spines['left'].set_visible(False)
ax.yaxis.tick_left()
ax.tick_params(labeltop='off') # don't put tick labels at the top
ax2.yaxis.tick_right()
# Make the spacing between the two axes a bit smaller
plt.subplots_adjust(wspace=0.15)
plt.show()
要添加断线
//效果，我们可以这样做(同样，从Paul Ivanov的示例进行了修改):import matplotlib.pylab as plt
import numpy as np
# If you're not familiar with np.r_, don't worry too much about this. It's just
# a series with points from 0 to 1 spaced at 0.1, and 9 to 10 with the same spacing.
x = np.r_[0:1:0.1, 9:10:0.1]
y = np.sin(x)
fig,(ax,ax2) = plt.subplots(1, 2, sharey=True)
# plot the same data on both axes
ax.plot(x, y, 'bo')
ax2.plot(x, y, 'bo')
# zoom-in / limit the view to different portions of the data
ax.set_xlim(0,1) # most of the data
ax2.set_xlim(9,10) # outliers only
# hide the spines between ax and ax2
ax.spines['right'].set_visible(False)
ax2.spines['left'].set_visible(False)
ax.yaxis.tick_left()
ax.tick_params(labeltop='off') # don't put tick labels at the top
ax2.yaxis.tick_right()
# Make the spacing between the two axes a bit smaller
plt.subplots_adjust(wspace=0.15)
# This looks pretty good, and was fairly painless, but you can get that
# cut-out diagonal lines look with just a bit more work. The important
# thing to know here is that in axes coordinates, which are always
# between 0-1, spine endpoints are at these locations (0,0), (0,1),
# (1,0), and (1,1). Thus, we just need to put the diagonals in the
# appropriate corners of each of our axes, and so long as we use the
# right transform and disable clipping.
d = .015 # how big to make the diagonal lines in axes coordinates
# arguments to pass plot, just so we don't keep repeating them
kwargs = dict(transform=ax.transAxes, color='k', clip_on=False)
ax.plot((1-d,1+d),(-d,+d), **kwargs) # top-left diagonal
ax.plot((1-d,1+d),(1-d,1+d), **kwargs) # bottom-left diagonal
kwargs.update(transform=ax2.transAxes) # switch to the bottom axes
ax2.plot((-d,d),(-d,+d), **kwargs) # top-right diagonal
ax2.plot((-d,d),(1-d,1+d), **kwargs) # bottom-right diagonal
# What's cool about this is that now if we vary the distance between
# ax and ax2 via f.subplots_adjust(hspace=...) or plt.subplot_tool(),
# the diagonal lines will move accordingly, and stay right at the tips
# of the spines they are 'breaking'
plt.show()
关于python - Python/Matplotlib-有没有办法制作不连续的轴？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/5656798/